Editor/Reviewer loginFrequency : 12 issues per year
Subject : Computer Applications and Technology
ISSN : 2319–8656 (Online)
IJCATR Volume 6 Issue 11
Intrusion Detection System Using Genetic Algorithm and Data Mining Techniques Based on the Reduction Features
Mohammad Ghalehgolabi , Amin Rezaeipanah
10.7753/IJCATR0611.1003
keywords : intrusion detection; genetic algorithm; distribution function; NSL-KDD; feature selection.
An intrusion detection system is the process for identifying attacks on network. Choosing effective and key features for intrusion detection is a very important topic in information security. The purpose of this study is to identify important features in building an intrusion detection system such that they are computationally effcient and effective. To improve the performance of intrusion detection system, this paper proposes an intrusion detection system that its features are optimally selected using genetic algorithm optimization. The proposed method is easily implemented and has a low computational complexity due to use of a simplified feature set for the classification. The extensive experimental results on the NSL-KDD intrusion detection benchmark data set demonstrate that the proposed method outperforms previous approaches, providing higher accuracy in detecting intrusion attempts and lower false alarm with reduced number of features.
@artical{m6112017ijcatr06111003,
Title = "Intrusion Detection System Using Genetic Algorithm and Data Mining Techniques Based on the Reduction Features",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "6",
Issue ="11",
Pages ="461 - 466",
Year = "2017",
Authors ="Mohammad Ghalehgolabi , Amin Rezaeipanah"}
The paper proposes an intrusion detection system for identifying attacks on network
Our goal is to identify important features in the development of an intrusion detection system
To improve the performance of intrusion detection system, using the genetic algorithm
The experimental results on the NSL-KDD intrusion detection data set is carried out.